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Model Selection

Given a set of candidate models, the goal of Model Selection is to select the model that best approximates the observed data and captures its underlying regularities. Model Selection criteria are defined such that they strike a balance between the goodness of fit, and the generalizability or complexity of the models.

Source: Kernel-based Information Criterion

Papers

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Showing 51–100 of 2050 papers

TitleStatusHype
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing dataCode1
Evaluating Weakly Supervised Object Localization Methods RightCode1
Triple equivalence for the emergence of biological intelligenceCode1
ExcelFormer: A neural network surpassing GBDTs on tabular dataCode1
Deep Domain Confusion: Maximizing for Domain InvarianceCode1
abess: A Fast Best Subset Selection Library in Python and RCode1
Adversarial Branch Architecture Search for Unsupervised Domain AdaptationCode1
Foundation Model is Efficient Multimodal Multitask Model SelectorCode1
Data Splits and Metrics for Method Benchmarking on Surgical Action Triplet DatasetsCode1
Hologram Reasoning for Solving Algebra Problems with Geometry DiagramsCode1
DisastIR: A Comprehensive Information Retrieval Benchmark for Disaster ManagementCode1
Hydra: A System for Large Multi-Model Deep LearningCode1
DATA: Domain-Aware and Task-Aware Self-supervised LearningCode1
CNN Model & Tuning for Global Road Damage DetectionCode1
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular dataCode1
Change is Hard: A Closer Look at Subpopulation ShiftCode1
cegpy: Modelling with Chain Event Graphs in PythonCode1
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation OverlapCode1
Data Models for Dataset Drift Controls in Machine Learning With Optical ImagesCode1
Distributed Out-of-Memory NMF on CPU/GPU ArchitecturesCode1
Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR ImagesCode1
BERTScore: Evaluating Text Generation with BERTCode1
Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM EvaluationCode1
Binary Bleed: Fast Distributed and Parallel Method for Automatic Model SelectionCode1
Bayesian Model Selection, the Marginal Likelihood, and GeneralizationCode1
Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian QuadratureCode1
BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion ModelsCode1
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular DataCode1
Additive Covariance Matrix Models: Modelling Regional Electricity Net-Demand in Great BritainCode1
Cardea: An Open Automated Machine Learning Framework for Electronic Health RecordsCode1
A comparison of methods for model selection when estimating individual treatment effectsCode1
BayesOpt Adversarial AttackCode1
clusterBMA: Bayesian model averaging for clusteringCode1
AD-LLM: Benchmarking Large Language Models for Anomaly DetectionCode1
Conditional Matrix Flows for Gaussian Graphical ModelsCode1
Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible EvaluationCode1
AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein EngineeringCode1
A Concise yet Effective model for Non-Aligned Incomplete Multi-view and Missing Multi-label LearningCode1
Automating Outlier Detection via Meta-LearningCode1
Data thinning for convolution-closed distributionsCode1
Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark StudyCode1
A General Model for Aggregating Annotations Across Simple, Complex, and Multi-Object Annotation TasksCode1
Deep Reinforcement Model Selection for Communications Resource Allocation in On-Site Medical CareCode1
DEGAN: Time Series Anomaly Detection using Generative Adversarial Network Discriminators and Density EstimationCode1
BarcodeBERT: Transformers for Biodiversity AnalysisCode1
Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science DomainsCode1
Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration ErrorCode1
Empirical evaluation of scoring functions for Bayesian network model selectionCode1
Entropic Descent Archetypal Analysis for Blind Hyperspectral UnmixingCode1
A Survey and Implementation of Performance Metrics for Self-Organized MapsCode1
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